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Detection of Moiré pattern in high-resolution images
Despite the improvements in the quality of digital images brought about by the development of digital cameras and smartphones, taking clean...
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Leveraging high-resolution remote sensing images for vehicle type detection using sparrow search optimization with deep learning
High-resolution remote sensing images (RSI) refer to images captured from a distance, usually from an aircraft or satellite that provide details...
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Crop-Guided Neural Network Segmentation of High-Resolution Skin Lesion Images
Medical images are often exceedingly large in width and height, limiting the maximum batch size when training convolutional neural networks and...
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Feature Aggregation Network for Building Extraction from High-Resolution Remote Sensing Images
The rapid advancement in high-resolution satellite remote sensing data acquisition, particularly those achieving sub-meter precision, has uncovered...
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SDPH: a new technique for spatial detection of path holes from huge volume high-resolution raster images in near real-time
Detecting and repairing road defects is crucial for road safety, vehicle maintenance, and enhancing tourism on well-maintained roads. However,...
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Multilevel detection and classification of diseased plant leaf images using high-resolution superlet transform and E-ResNet
Plant leaf disease detection in early stage is a very challenging task that and is one of the most promising research areas in the field of precision...
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High-resolution SVBRDF estimation based on deep inverse rendering from two-shot images
The surface of a large number of objects in the real world shows the characteristics of stationary material. These appearances usually frequently...
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PMNet: a multi-branch and multi-scale semantic segmentation approach to water extraction from high-resolution remote sensing images with edge-cloud computing
In the field of remote sensing image interpretation, automatically extracting water body information from high-resolution images is a key task....
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BliMSR: Blind Degradation Modelling for Generating High-Resolution Medical Images
A persisting problem with existing super-resolution (SR) models is that they cannot produce minute details of anatomical structures, pathologies, and...
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Fusion of UNet and ResNet decisions for change detection using low and high spectral resolution images
Image change detection is an active research topic in the field of remote sensing, as it allows monitoring environmental changes that occur on...
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High-Resolution Imaging Satellite Constellation
Large-scale Low-Earth Orbit (LEO) satellite constellations have wide applications in communications, surveillance, and remote sensing. Along with the...
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Creating High-Resolution Adversarial Images Against Convolutional Neural Networks with the Noise Blowing-Up Method
Convolutional Neural Networks (CNNs) are widely used for image recognition tasks but are vulnerable to attacks. Most existing attacks create...
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Extraction Method of Rotated Objects from High-Resolution Remote Sensing Images
In recent years, the rapid development of remote sensing technology has made intelligent interpretation possible. However, remote sensing images have...
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Individual tree crown delineation in high-resolution remote sensing images based on U-Net
We present a deep learning-based framework for individual tree crown delineation in aerial and satellite images. This is an important task, e.g., for...
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HAZE-Net: High-Frequency Attentive Super-Resolved Gaze Estimation in Low-Resolution Face Images
Although gaze estimation methods have been developed with deep learning techniques, there has been no such approach as aim to attain accurate...
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Hyperspectral image super-resolution using multi-scale decomposition and convolutional neural network based on relation type between low- and high-resolution images
Hyperspectral images (HSIs) usually have high spectral resolution and low spatial resolution. 3D convolutional neural networks (3D-CNNs) can...
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Presswork defect inspection using only defect-free high-resolution images
Efficient automated presswork defect detection is valuable to the printing industry since such defects dramatically depress the presswork grad and...
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A hybrid CUDA, OpenMP, and MPI parallel TCA-based domain adaptation for classification of very high-resolution remote sensing images
Domain Adaptation (DA) is a technique that aims at extracting information from a labeled remote sensing image to allow classifying a different image...
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Micro-scale searching algorithm for high-resolution image matting
Natural image matting based on pixel pair optimization is commonly employed during image post-processing. However, obtaining high-quality alpha...
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SAR2EO: A High-Resolution Image Translation Framework with Denoising Enhancement
Synthetic Aperture Radar (SAR) to electro-optical (EO) image translation is a fundamental task in remote sensing that can enrich the dataset by...